code: def testTraining(self):
      rlt = rl_tuner.RLTuner(
          self.output_dir,
          note_rnn_checkpoint_dir=self.checkpoint_dir,
          output_every_nth=30,
      )
      rlt.train(num_steps=31, exploration_period=3)
  
      checkpoint_dir = os.path.dirname(rlt.save_path)
      checkpoint_files = [
          f
          for f in os.listdir(checkpoint_dir)
          if os.path.isfile(os.path.join(checkpoint_dir, f))
      ]
      checkpoint_step_30 = [
          f
          for f in checkpoint_files
          if os.path.basename(rlt.save_path) + "-30" in f
      ]
  
      self.assertTrue(len(checkpoint_step_30))
  
      self.assertTrue(len(rlt.rewards_batched) >= 1)
      self.assertTrue(len(rlt.eval_avg_reward) >= 1)
  
file_path: magenta/magenta/models/rl_tuner/rl_tuner_test.py
imports: import os
  import os.path
  import tempfile
  from magenta.models.rl_tuner import note_rnn_loader
  from magenta.models.rl_tuner import rl_tuner
  import matplotlib
  import matplotlib.pyplot
  import tensorflow.compat.v1
label_desc: Use image node_id 7 for calling the RLTunerTest obj's underlying member method code with example usage: obj.testTraining() without return types